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Search results for: MOLECULAR IMAGING
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Development of biocompatible iron oxide-silicon oxide core-shell nanoparticles as subcellular delivery platform for glucosamine-6-phosphate synthase inhibitors
PublicationIn order to develop the preparation of iron oxide-silica coreshell nanoparticles (CSNPs), thesis deeply explores the cetyltrimethylammonium (CTA+) directed silica coating methods of the oleic-acid capped iron oxide nanoparticles (OA-IONPs) initialized under near-neutral pH conditions. It is demonstrated that the initial alkaline hydrolysis of ethyl acetate in the presence of CTA+ and OA-IONPs induces an unusual ligand exchange...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Optymalizacja sygnału testującego dla potrzeb identyfikacji modeli procesów biologicznych i medycznych
PublicationRozprawa poświęcona jest optymalizacji sygnału testującego dla celów identyfikacji modeli procesów biologicznych i medycznych. Zagadnienie to zawiera się w szerszym zagadnieniu optymalizacji eksperymentu, polegającym na poszukiwaniu tej wartości wybranej zmiennej eksperymentu (w rozprawie jest to sygnał testujący), która zapewni maksimum obranego kryterium optymalności. Optymalizacja eksperymentu jest szczególnie istotna w zastosowaniach...